Université de Lorraine, CNRS, LPCT , F-54000 Nancy , France.
Department of Chemistry , Middle East Technical University , 06800 , Ankara , Turkey.
J Chem Inf Model. 2019 Jan 28;59(1):206-214. doi: 10.1021/acs.jcim.8b00605. Epub 2018 Nov 27.
Semi-empirical quantum methods from the neglect of differential diatomic overlap (NDDO) family such as MNDO, AM1, or PM3 are fast albeit approximate quantum methods. By combining them with linear scaling methods like the divide & conquer (D&C) method, it is possible to quickly evaluate the energy of systems containing hundreds to thousands of atoms. We here present our implementation in the Amber biomolecular package of a SEBOMD module that provides a way to run semi-empirical Born-Oppenheimer molecular dynamics. At each step of a SEBOMD, a fully converged self-consistent field (SCF) calculation is performed to obtain the semiempirical quantum potential energy of a molecular system encaged or not in periodic boundary conditions. We describe the implementation and the features of our SEBOMD implementation. We show the requirements to conserve the total energy in NVE simulations, and how to accelerate SCF convergence through density matrix extrapolation. Specific ways of handling periodic boundary conditions using mechanical embedding or electrostatic embedding through a tailored quantum Ewald summation is developed. The parallel performance of SEBOMD simulations using the D&C scheme are presented for liquid water systems of various sizes, and a comparison between the traditional full diagonalization scheme and the D&C approach for the reproduction of the structure of liquid water illustrates the potentiality of SEBOMD to simulate molecular systems containing several hundreds of atoms for hundreds of picoseconds with a quantum mechanical potential in a reasonable amount of CPU time.
半经验量子方法忽略了双原子重叠（NDDO）家族，例如 MNDO、AM1 或 PM3，它们是快速的，尽管是近似的量子方法。通过将它们与线性标度方法（如分治（D&C）方法）结合使用，可以快速评估包含数百到数千个原子的系统的能量。我们在这里介绍了在 Amber 生物分子包中实现的 SEBOMD 模块，该模块提供了一种运行半经验 Born-Oppenheimer 分子动力学的方法。在 SEBOMD 的每一步中，都执行完全收敛的自洽场（SCF）计算，以获得分子系统的半经验量子势能，该分子系统被封装在周期性边界条件中或未被封装在周期性边界条件中。我们描述了我们的 SEBOMD 实现的实现和功能。我们展示了在 NVE 模拟中保持总能量的要求，以及如何通过密度矩阵外推加速 SCF 收敛。通过定制的量子 Ewald 求和，开发了使用机械嵌入或静电嵌入处理周期性边界条件的特定方法。展示了使用 D&C 方案进行 SEBOMD 模拟的并行性能，针对各种大小的液态水系统，并比较了传统的完全对角化方案和 D&C 方法在复制液态水结构方面的性能，说明了 SEBOMD 模拟包含数百个原子的分子系统的潜力在合理的 CPU 时间内使用量子力学势模拟数百个皮秒。
